STCO 426: Blog Post #3

Chapter three of Paharia’s (2013) book Loyalty 3.0: How big data and gamification are revolutionizing customer and employee engagement was extremely informative on the topic of big data, giving enough detail to have a general understanding of what big data is and the capabilities it has. Paharia started off this chapter with a look at where big data fits into the grand scheme of Loyalty 3.0. It is the second building block in the equation to obtain loyal customers (Paharia).

Paharia (2013) talked about how big data is this gigantic amount of information that can be found on people, businesses, and more that continues to grow. It has been made possible by technological advances like mobile phones (Paharia). Big data has not been around for very long (Paharia). Other types of data existed previously with information like customer addresses and purchase history, but now data has expanded dramatically with so much activity being online (Paharia). According to Paharia, there are a variety of places big data comes from including, “mobile phone usage, online shopping patterns, social networks, radio-frequency identification (RFID) chips, sensors and connected devices, mentions in blog posts, customer feedback, and other ‘public’ information you create or read from the Internet” (p. 41).

Paharia (2013) sees big data in a positive light as a way to help businesses know their customers. This allows for more effective ways of marketing to reach the target audience based on data about them (Paharia).

Paharia (2013) gives multiple ways that big data can be used. One way to use big data is to do a cluster analysis (Paharia). It can be helpful to see what clusters people fall into to find a group to market to and know how to market to them (Paharia). Another way to use big data is to do A/B testing (Paharia). Paharia discusses how A/B testing can be used to figure out which option achieves the best outcome. A third way given by Paharia to use big data is through crowdsourcing. Crowdsourcing is letting unknown people help with some task (Paharia). Predictive modeling is another way given by Paharia which is about being able to make an educated guess of people’s future actions in a situation by using data. Paharia discusses sentiment analysis which is about analyzing data in an attempt to determine how people feel about something. Stream processing is written about by Paharia next which is about using the data streams for specific purposes. Big data can also be used to discover outliers and things that are similar to other things (Paharia). Lastly, Paharia writes about how big data can be used to look at groups of similar people.

Paharia (2013) gives tools that can be used to process big data. Paharia writes about NoSQL, a type of database used to process a lot of big data when the information does not need to be reliable all of the time. Paharia also writes about Hadoop, software that is also used for big data. Paharia recognizes that there are visual tools as well that can be used to help see the information.

Paharia (2013) also dives into how businesses can utilize big data with consumers and with employees. For consumers, this includes techniques like microsegmentation and recommendation engines (Paharia). For the newer realm of using big data on employees, this includes using big data for choosing new talent and for seeing how the performance of employees compares against the performance of employees of the same business and other businesses (Paharia). This comparison with big data can be unsettling to me as everyone is different, and I would hope it would not come to a point where people that are slower than others have trouble finding a job.

With all this big data that has been created, one might wonder about the safety of all the information. Rawat et al. (2021) write, “When data gets really big, securing it becomes really difficult” (p. 2063). Their article provides ways of protecting big data. In conclusion, I am interested to see how big data evolves and is dealt with over the years to come.

References

Paharia, R. (2013). Loyalty 3.0: How big data and gamification are revolutionizing customer and employee engagement. McGraw-Hill.

Rawat, D. B., Doku, R., & Garuba, M. (2021). Cybersecurity in big data era: From securing big data to data-driven security. IEEE Transactions on Services Computing, 14(6), 2055–2072, https://doi.org/10.1109/TSC.2019.2907247